Schedule: Internet of Things sessions

Cheap networks, smart phones and a world of sensors herald an Internet that’s always connected, always on, and nothing like the world of today. And, it’s not just people who are connected, ubiquitous computing means devices are connected, controllable and creating reams of data. We’ll look at the impact of the Internet of Things and how the data ecosystem is gearing up to handle and learn from the onslaught of new data sources.

Location: 116
Marco Puts (Statistics Netherlands), Martijn Tennekes (Statistics Netherlands), Piet Daas (Statistics Netherlands)
Average rating: ***..
(3.25, 8 ratings)
We show how to use road sensor data for making reliable statistics about traffic intensities on the 3000 km long Dutch motorways. To use the data of 20.000 road sensors, dimension reduction is applied on the sensor data, which is highly redundant, for compensating the poor quality of the data. Read more.
Location: 116
Assaf Araki (Intel)
Average rating: ***..
(3.33, 3 ratings)
IoT analytic brings an engineering and analytic complexity to the new market solutions.In this session we will share the learnings from the development of Intel's Cloud IoT Analytics Platform based on open source software.We will share learning from the product development and present use case in the Parkinson Disease research, leverages wearable sensors to monitor PD patient’s activities,24/7. Read more.
Location: 116
Jodok Batlogg (CRATE Technology GmbH)
Creating a backend for data intensive apps requires gluing several technologies together, which isn’t always simple, cheap or scalable. The world of sensor and IoT data, together with privacy concerns (mostly European), and the need to make contextual sense of it all, presents an opportunity to bring in the post-hadoop era and democratise data stores. Read more.
Location: 116
Vincent Spruyt (Argus Labs), Ann Wuyts (Sentiance), Filip Maertens
Average rating: ****.
(4.67, 6 ratings)
We’ll explain how we’re automatically deriving a person’s mood and personality from mobile sensor data, and how we map and quantify these so that it becomes possible for technology to understand and work with ‘how we feel’. We'll cover the technical details of the data gathering setup, our data-mining and machine learning approaches, and the big-data processing architecture developed. Read more.